kingchenc
8a103ef920
* feat(data-layer): TickAggregator in Node, WASM, Python + C ABI hub First data-layer feature (F2): roll trade ticks up into fixed-timeframe OHLCV candles, exposed natively and over the C ABI. - wickra-data wired as a binding dependency (workspace dep; its wickra-core dep is default-features=false so it never forces rayon into the rayon-free WASM build — native bindings re-enable parallel through their own dependency). - Node `TickAggregator(bucket, gapFill?)` -> `push(price, size, ts): Candle[]`; WASM the same (array of objects); Python `push(...) -> list[tuple]`. - C ABI: `WickraCandle` struct + `wickra_tick_aggregator_new/push/free` (push writes candles into a caller buffer and returns the count), generated via the capi generator's new DATA_LAYER section; cbindgen now parses wickra-data so `TickAggregator` is a forward-declared opaque; header vendored to bindings/go. Verified bit-identical across Node/WASM/Python/C/C++ (o=100 h=101 l=100 c=101 v=3 ts=0 for the shared 3-tick probe). WIP: Go/C#/Java/R generated bindings and the cross-language golden are still pending. * feat(data-layer): TickAggregator in Go, C#, Java, R (lossless push/drain) Complete F2 across all 10 languages: the C-ABI tick aggregator now uses a two-step push/drain so gap-fill candles are never lost, and the four generated bindings expose it idiomatically. - C ABI redesigned: opaque TickAggregator handle (inner aggregator + pending buffer); push consumes a tick and returns the closed-candle count, drain copies them into a count-sized caller buffer. - Go: NewTickAggregator + Push(price,size,ts) []Candle; C#: TickAggregator + Candle[] Push(...); Java: TickAggregator + Candle[] push(...); R: TickAggregator constructor + push() S3 generic returning an (n x 6) numeric matrix. - Candle output record generated per language from WickraCandle. Verified bit-identical to the native bindings (o=100 h=101 l=100 c=101 v=3 ts=0) in Go, C#, Java, and R at runtime; R passes R CMD check (pre-existing doc warnings only). WIP: cross-language data-layer golden + CHANGELOG still pending. * test(data-layer): cross-language golden for the tick aggregator + CHANGELOG gen_golden emits a deterministic tick stream (testdata/golden/data_ticks.csv) and the reference candle streams with and without gap filling (data_candles.csv, data_candles_gap.csv). Every binding replays the shared ticks through its TickAggregator and checks the candles bit-for-bit (fp tolerance) against the Rust reference: - Node / WASM / Python / Go / C# / Java / R: a dedicated parity test each. - C / C++: data_layer_test.c (compiled as both, run as ctest). The gap-fill fixture closes several candles from a single push, exercising the lossless push/drain path. Records the feature under CHANGELOG [Unreleased]. * fix(examples): rename the CSV-loader candle to WickraBar The example CSV helper (wickra_csv.h) defined its own struct WickraCandle, which now collides with the public C ABI WickraCandle (the tick aggregator output) in any example that includes both headers (backtest, multi_timeframe, the strategy examples). The public type owns the name; rename the example loader's bar to WickraBar. The generated golden_test.c is untouched (its only match was the unrelated WickraCandleVolumeOutput).
Wickra — R 
Streaming-first technical indicators for R, over the Wickra C ABI hub via .Call.
Wickra is a multi-language technical-analysis library with a Rust core and
bindings for Python, Node.js and WASM, plus a C ABI for C, C++, C#, Go, Java, R
and any other C-capable language. Every indicator is an O(1) streaming state
machine, so live trading and historical backtests share the exact same
implementation. This package is the R binding; it reaches the C ABI hub through
R's native .Call interface and exposes all 514 indicators as constructors that
return a lightweight wickra_indicator object.
Install
The package compiles a thin C glue layer (.Call) against the prebuilt Wickra
C ABI library, so a C toolchain (Rtools on Windows) is required, plus the C ABI
header and library. Build the library from the workspace, then install the
package pointing at it:
cargo build -p wickra-c --release
WICKRA_INCLUDE_DIR="$PWD/bindings/c/include" \
WICKRA_LIB_DIR="$PWD/target/release" \
R CMD INSTALL bindings/r
On Windows the C ABI DLL is bundled into the package and put on the load path automatically; on Linux and macOS the library path is baked in via rpath.
Quick start
library(wickra)
# Batch: run an indicator over a whole series (NaN at warmup positions).
prices <- 100 + (0:999) * 0.1
sma <- Sma(20)
values <- batch(sma, prices)
# Streaming: the same indicator, fed one observation at a time in O(1).
rsi <- Rsi(14)
for (price in prices) {
v <- update(rsi, price) # NaN during warmup
if (!is.na(v) && v > 70) message("overbought")
}
# Multi-output indicators return a named vector (NA while warming up).
macd <- MacdIndicator(12, 26, 9)
update(macd, 42) # c(macd = NA, signal = NA, histogram = NA)
batch(ind, prices) and feeding the same prices through update() produce
identical values — the equivalence is enforced by the test suite. Candle-input
indicators take the OHLCV fields plus a timestamp, e.g.
update(atr, open, high, low, close, volume, timestamp). The native handle is
freed automatically when the object is garbage-collected.
Benchmark
benchmarks/throughput.R reports streaming and batch updates-per-second for
SMA, ATR and MACD. It measures this binding's FFI overhead, not a
cross-library ratio (the same Rust core runs under every binding) — see the
repository BENCHMARKS.md §3.
Rscript benchmarks/throughput.R
Documentation
The full indicator catalogue, guides, quickstarts, and API reference live in the main repository and documentation site:
- Repository & full indicator list: https://github.com/wickra-lib/wickra
- Docs (quickstarts, cookbook, TA-Lib migration): https://docs.wickra.org
- Runnable examples:
examples/r/
Wickra ships native bindings for Python, Node.js, WASM and Rust, plus a
C ABI hub that any C-capable language (C, C++, C#, Go, Java, R) links against —
all exposing the same indicators from the shared, unsafe-forbidden Rust core.
Security
Found a security issue? Please don't open a public issue. Report it privately
via the affected repository's Security tab ("Report a vulnerability") or email
support@wickra.org with a subject line starting [wickra security]. Full
policy: https://github.com/wickra-lib/wickra/blob/main/SECURITY.md.
Disclaimer
Wickra is an indicator toolkit, not a trading system. The values it computes are deterministic transforms of the input data — they are not financial advice and do not predict the market. Any use in a live trading context is at your own risk. The library is provided as is, without warranty of any kind.
License
Licensed under either of Apache-2.0 or MIT at your option.